Nuriziani Hussin
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Preferred name
Nuriziani Hussin
Official Name
Nuriziani, Hussin
Alternative Name
Hussin, Nuriziani
Hussin, N.
Main Affiliation
Scopus Author ID
26633116700
Researcher ID
DVD-9074-2022

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  • Publication
    Analysis of space charge formation in LDPE in the presence of crosslinking byproducts
    ( 2012-02)
    Nuriziani Hussin
    ;
    George Chen
    Cross-linking byproducts are suspected to be the main contributing factor in space charge formation observed in XLPE. To investigate the mechanism behind this phenomenon, low density polyethylene was soaked into three main crosslinking byproducts, acetophenone, α- methylstyrene and cumyl alcohol, and space charge measurements were performed using the Pulse Electroacoustic technique (PEA). It has been found that soaking LDPE in cumyl alcohol introduces more charges into the system, with homocharges and heterocharges accumulating within the sample compared to the additive free sample. In contrast, α- methylstyrene and acetophenone reduce the amount of accumulated charges. In terms of charge decay, all three byproducts enhance the decay process in the insulator. Further investigations were conducted in conditions where two byproducts are present in a sample. The results shows that acetophenone is a dominant byproduct in determining the charge density patter built up during the charging process, whilst the rate of charge decay is observed to be high in the presence of α-methylstyrene in the sample.
  • Publication
    Flashover voltage prediction on polluted cup-pin the insulators under polluted conditions
    ( 2021-01-01)
    Salem A.A.
    ;
    Abd-Rahman R.
    ;
    Kamarudin M.S.
    ;
    Othman N.A.
    ;
    Jamail N.A.M.
    ;
    Nuriziani Hussin
    ;
    Haziah Abdul Hamid
    ;
    Rawi I.M.
    The natural pollution which is mainly affected by the weather conditions are the main cause of flashovers on high voltage insulators leading to outages in power systems. In this work, characteristics of flashover for contaminated cup-pin insulators have been studied based on experiential test and a mathematical model. Information from laboratory test combined with new mathematical model results are used to define Artificial Neural Network (ANN) algorithm and Adaptive Neuro-fuzzy Inference System (ANFIS) for calculated the flashover characteristics (current IF and voltage UF). several of experiments and measurement are carried out for 1:1, 5:1, 10:1 and 15:1 ratios of bottom to top surface salt deposit density on contaminated samples (z). Dimensional Analysis Method (DAM) was used to derive new model for the variables which often effective in the flashover phenomenon of polluted insulators. The model was derived by establishment the relationship between flashover voltage UF and current IF, length of pollution layer LP, exposure time t, arc constant A and layer pollution conductivity of insulator σ. The both arc constants A and n is computed using genetic algorithm. Comparative investigates have clearly shown that the approach AI-based method gives the agreeable results compared to the mathematical model.